Authenticating based on behavioral transactional patterns
AssigneeCapital One Services, LLC
InventorsJoshua Edwards, David Septimus, Samuel Rapowitz, Jenny Melendez, Tyler Maiman, Viraj Chaudhary
Life of this patent
Estimating the term…
Abstract
Aspects described herein may allow for authenticating a user by generating a customized set of authentication questions based on patterns that are automatically detected and extracted from user data. The user data may include transaction data collected over a period of time. By automatically detecting user patterns that correspond to user behavior over a period of time, an authentication system may be able to generate information that is recognizable to an authentic user but difficult to guess or circumvent for any other user.
Claims20
A method comprising:
- receiving, from a user device, a request for access to an account associated with a user;
- retrieving transaction data for the account, wherein the transaction data indicates a plurality of transactions;
- generating, based on the transaction data, for each transaction of the plurality of transactions, machine learning inputs;
- providing the machine learning inputs to a machine learning algorithm to yield one or more machine learning outputs;
- generating, based on the one or more machine learning outputs, a spending pattern associated with the user;
- determining a deviation between:
- the spending pattern associated with the user, and
- a spending pattern for an average user;
- generating, based on the deviation, a question to authenticate the user;
- receiving, from the user device, a response to the question;
- and
- providing, to the user device and based on the response to the question, access to the account.
A computing device comprising:
- one or more processors;
- and
- memory storing instructions that, when executed by the one or more processors, cause the computing device to:
- receive, from a user device, a request for access to an account associated with a user;
- retrieve transaction data for the account, wherein the transaction data indicates a plurality of transactions;
- generate, based on the transaction data, for each transaction of the plurality of transactions, machine learning inputs;
- provide the machine learning inputs to a machine learning algorithm to yield one or more machine learning outputs;
- generate, based on the one or more machine learning outputs, a spending pattern associated with the user;
- determine a deviation between:
- the spending pattern associated with the user, and
- a spending pattern for an average user;
- generate, based on the deviation, a question to authenticate the user;
- receive, from the user device, a response to the question;
- and
- provide, to the user device and based on the response to the question, access to the account.
One or more non-transitory computer-readable media storing instructions that, when executed by one or more processors, cause a computing device to:
- receive, from a user device, a request for access to an account associated with a user;
- retrieve transaction data for the account, wherein the transaction data indicates a plurality of transactions;
- generate, based on the transaction data, for each transaction of the plurality of transactions, machine learning inputs;
- provide the machine learning inputs to a machine learning algorithm to yield one or more machine learning outputs;
- generate, based on the one or more machine learning outputs, a spending pattern associated with the user;
- determine a deviation between:
- the spending pattern associated with the user, and
- a spending pattern for an average user;
- generate, based on the deviation, a question to authenticate the user;
- receive, from the user device, a response to the question;
- and
- provide, to the user device and based on the response to the question, access to the account.
Dependencies are inferred from the claim text.